{"id":"W4298033315","doi":"","title":"An illustrated glossary of ambiguous PLM terms used in discrete manufacturing","year":2015,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Glossary; Manufacturing engineering; Engineering; Computer science; Linguistics; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001463709,0.002400801,0.001493072,0.007178737,0.002089606,0.004243864,0.001519123,0.00210046,0.06776328],"category_scores_gemma":[0.006485792,0.0006628475,0.001018108,0.01270093,0.001765796,0.004063882,0.002082189,0.003234504,0.03795896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001767399,"about_ca_system_score_gemma":0.001696097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004123784,"about_ca_topic_score_gemma":0.00554469,"domain_scores_codex":[0.9984993,0.0003935594,0.0004218442,0.0002152589,0.0003725163,0.00009749243],"domain_scores_gemma":[0.9957706,0.002727779,0.0003853627,0.0002789519,0.0007307768,0.0001065109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003039221,0.00005625831,0.0004387701,0.007467761,0.00004144475,0.001255372,0.0025668,0.001687822,0.008450956,0.2157352,0.5920777,0.1699179],"study_design_scores_gemma":[0.000006475705,0.00001173597,0.0002116338,0.0007878104,0.000007909857,0.0003987056,0.000171704,0.000334331,0.0004687137,0.006627009,0.9909541,0.00001969855],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.008108724,0.1009529,0.2884484,0.01203678,0.02356887,0.001399338,0.08342835,0.005913188,0.4761435],"genre_scores_gemma":[0.112143,0.1026873,0.4659157,0.01712607,0.009716718,0.003691084,0.08800798,0.01217034,0.1885419],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06776328,"threshold_uncertainty_score":0.2266908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013006791479581,"score_gpt":0.2125055171050386,"score_spread":0.1994987256254576,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}